The document discusses how organizations can unleash the promises of big data. It defines big data and how it differs from traditional small data. The presentation covers how big data is impacting industries and provides steps for organizations to start their big data journey, including starting with a business problem, developing a data framework and strategy, understanding existing data assets, and building analytical capabilities. Success stories and lessons learned are presented, along with common hurdles organizations may face with big data.

1. HOW TO UNLEASH
THE PROMISES OF BIG
DATA WITHIN AN
ORGANIZATION?

2. LET’S KNOW EACH OTHER
From your smart phones, open the following website:
slido.com
Enter the event code:
#E963
Answer the poll questions (3)
Ask questions

3. “NUMBERS/ DATA HAVE AN IMPORTANT STORY TO
TELL. THEY RELY ON YOU TO GIVE THEM A
VOICE”- STEPHEN FEW

4. WHAT WE WILL COVER IN THIS PRESENTATION?
❑ What is Big Data?
❑ How is it different from “small data”?
❑ Why we are discussing it?
❑ How is it impacting our lives?
❑ Where does it apply?
❑ Steps to start your big data journey
❑ Success stories and lessons learned

5. DATA, INFORMATION, KNOWLEDGE, & WISDOM (DIKW)

6. THE DIKW CONTINUUM

7. WHAT IS BIG DATA? AND WHY IT’S BIG?

9. DATA NEVER SLEEPS
Over 2.5 quintillion bytes of data are created every single day!

11. WHAT ARE THE PROMISES OF BIG DATA?

12. ❑ Better targeting of marketing efforts
❑ Reduce cost
❑ Improve productivity
❑ Getting a better read on performance
❑ Building customer engagement
❑ Enable prediction and forecasting

13. BIG DATA, BUSINESS INTELLIGENCE,
CLOUD COMPUTING & ANALYTICS LEAD

14. WHERE DOES IT APPLY?

15. INDUSTRIES THAT ARE BEING RADICALLY
TRANSFORMED BY THE ADOPTION OF BIG
DATA
❑ Energy
❑ Real Estate
❑ Insurance
❑ Music
❑ Aviation
❑ Telecom
❑ Consumer Goods
❑ Hospitality
❑ Gaming
❑ IT
❑ Health Care
❑ Humanitarian
And much more…..

16. HOW TO GET STARTED WITH BIG DATA?

17. ONE SIZE DOES NOT FIT ALL
Several years ago, Big Data’s pitch to the business world went something like this:
❑ Collect Everything
❑ Apply Computational Processing Power
❑ Magic will happen
❑ Profit

18. WE RECOMMEND THE FOLLOWING STEPS TO
START YOUR BIG DATA JOURNEY
❑ Start with a business problem and a goal
❑ Research to learn where and how advanced analytics is most likely to help your
business
❑ Benchmark your industry and determine your company’s current position in analytics
❑ Develop a data framework: imagining how to use big data and how to apply the
insights derived from big data analytics to further your business
❑ Develop a data strategy: Which business decisions do you want to improve? And
which customer touchpoints do you want to optimize?
❑ Understand what data assets you have

19. ❑ Build analytical capability and culture across the organization.
❑ Foster collaboration and partnerships
❑ Encourage experimentation, brainstorming
❑ Run your project in sprints with tangible and measurable outcomes

20. DATA STRATEGY
❑ Practical
❑ Relevant
❑ Evolutionary
❑ Connected/integrated

21. RICHTER’S DATA FOR 2018
> 70 Clients
> 14 K Post
> 1 M followers
> 3 M interactions

22. SUCCESS STORIES
❑ Amazon
❑ Facebook
❑ Walmart
❑ Netflix
❑ Dubai
❑ Arabia Weather

23. LESSONS LEARNED
❑ Google Flu
❑ Cambridge Analytica
❑ Walmart

24. HURDLES
❑ The tools for making sense of data are not very usable or affordable
❑ A substantial skill shortage
❑ Poor data quality
❑ Data privacy

25. AT THE MOMENT LESS THAN 0.5% OF ALL DATA IS EVER
ANALYSED AND USED.

26. THE ASPIRATION – FUTURE OF BIG DATA
❑ Big data will turn out to rich smart data
❑ Tackle pressing issues in real time
❑ Get governed with laws
❑ Create open source data solutions that enable non-experts to take part in the data
science revolution

27. CONCLUSION
❑ Before Jumping into Big Data, know Where and How You’re Jumping
❑ It's not the amount of data that's important: it's what organisations do with the data that matters
❑ Creates an environment where people are empowered to use the data instead of just getting it
❑ Context is critical: Considering the context and meaning of data – not just the data itself
❑ Not all data is created equal. Quality matters.
❑ Big Data helps you find the questions you don’t know you want to ask
❑ Any given dataset can tell many different stories depending on the questions we ask of it and the filters we
apply to answer those questions
❑ Beyond Big Data, Human Interpretation still counts
❑ Read trends and case studies to see how Big Data is impacting the way we do business

28. QUESTIONS?

29. LET’S CONTINUE THE CONVERSATION – REACH
OUT THROUGH:
E-mail: yarajubran@ymail.com
LinkedIn: www.linkedin.com/in/yarajubran